1. Field of the Invention
The present invention relates to a method and a system for estimating quantities of particulates emitted in the exhaust gases of a diesel engine of a motor vehicle.
The estimation of the quantities of particulates emitted in the exhaust gases of a diesel engine of a motor vehicle is useful for managing engine control and for regenerating the pollution control means (particulate filters), as accurately and economically as possible.
2. Description of the Related Art
Present computer models consume a considerable amount of computer time, and are inaccurate. It is often unfeasible to mount these models in a vehicle because of their computational complexity and the memory size necessary. Their drastic simplification severely jeopardizes estimation performance.
Mapping estimation models exist. The number of parameters affecting these estimations is relatively large. Two-dimensional mapping management demands the arrangement of several mappings, including correction mappings, making the estimation complex. Moreover, the addition of mappings behind one another does not allow a description of the operating space in the same way as a model with more than two inputs. Such models are also difficult to calibrate. Furthermore, the mapping models fail to account for dynamic phenomena which are very important for these estimations.
Models used on computers also exist, but not on an onboard computer, because the little memory available on an onboard computer implies computation times incompatible with real time. These models fail to account for the limited power of the computers. They sometimes use input measurements that are unknown on a vehicle, and it is unfeasible to add just any sensor, assuming that this is technically possible, on a vehicle. These models may also be recursive, and incur risks of divergent estimations.
The document “Virtual Sensors: A real-time neural network-based intelligent performance and emissions prediction system for on-board diagnostics and engine control” by Chris Atkinson and Mike Traver, describes a method for predicting releases in exhaust gases. This method calculates the rate of instantaneous releases which are too inaccurate to use their cumulative value to trigger action.
The document “Prediction of emissions from a turbocharged passenger car diesel engine using a neural network” by C. J. Brace, M. Deacon, N. D. Vaughan, J. Charlton, and C R Burrows, describes an estimation by mapping that is too inaccurate and fails to account for dynamic phenomena, as explained above.
The document “Prediction of Diesel Engine Exhaust Emissions using Artificial Neural Networks”, by Chris Brace, describes a system that is difficult to mount on a vehicle, uses inputs unavailable on a vehicle, and it is unfeasible to add just any sensor, presuming that it is technically possible.